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Article: Vehicle-component identification based on multiscale textural couriers

TitleVehicle-component identification based on multiscale textural couriers
Authors
KeywordsFeature-point extraction
Image segmentation
Texture analysis
Vehicle occlusion
Vehicle-component identification
Issue Date2007
PublisherI E E E. The Journal's web site is located at http://www.ewh.ieee.org/tc/its/trans.html
Citation
Ieee Transactions On Intelligent Transportation Systems, 2007, v. 8 n. 4, p. 681-694 How to Cite?
AbstractThis paper presents a novel method for identifying vehicle components in a monocular traffic image sequence. In the proposed method, the vehicles are first divided into multiscale regions based on the center of gravity of the foreground vehicle mask and the calibrated-camera parameters. With these multiscale regions, textural couriers are generated based on the localized variances of the foreground vehicle image. A new scale-space model is subsequently created based on the textural couriers to provide a topological structure of the vehicle. In this model, key feature points of the vehicle can significantly be described based on the topological structure to determine the regions that are homogenous in texture from which vehicle components can be identified by segmenting the key feature points. Since no motion information is required in order to segment the vehicles prior to recognition, the proposed system can be used in situations where extensive observation time is not available or motion information is unreliable. This novel method can be used in real-world systems such as vehicle-shape reconstruction, vehicle classification, and vehicle recognition. This method was demonstrated and tested on 200 different vehicle samples captured in routine outdoor traffic images and achieved an average error rate of 6.8% with a variety of vehicles and traffic scenes. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/57456
ISSN
2015 Impact Factor: 2.534
2015 SCImago Journal Rankings: 1.300
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLam, WWLen_HK
dc.contributor.authorPang, CCCen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2010-04-12T01:37:13Z-
dc.date.available2010-04-12T01:37:13Z-
dc.date.issued2007en_HK
dc.identifier.citationIeee Transactions On Intelligent Transportation Systems, 2007, v. 8 n. 4, p. 681-694en_HK
dc.identifier.issn1524-9050en_HK
dc.identifier.urihttp://hdl.handle.net/10722/57456-
dc.description.abstractThis paper presents a novel method for identifying vehicle components in a monocular traffic image sequence. In the proposed method, the vehicles are first divided into multiscale regions based on the center of gravity of the foreground vehicle mask and the calibrated-camera parameters. With these multiscale regions, textural couriers are generated based on the localized variances of the foreground vehicle image. A new scale-space model is subsequently created based on the textural couriers to provide a topological structure of the vehicle. In this model, key feature points of the vehicle can significantly be described based on the topological structure to determine the regions that are homogenous in texture from which vehicle components can be identified by segmenting the key feature points. Since no motion information is required in order to segment the vehicles prior to recognition, the proposed system can be used in situations where extensive observation time is not available or motion information is unreliable. This novel method can be used in real-world systems such as vehicle-shape reconstruction, vehicle classification, and vehicle recognition. This method was demonstrated and tested on 200 different vehicle samples captured in routine outdoor traffic images and achieved an average error rate of 6.8% with a variety of vehicles and traffic scenes. © 2006 IEEE.en_HK
dc.languageengen_HK
dc.publisherI E E E. The Journal's web site is located at http://www.ewh.ieee.org/tc/its/trans.htmlen_HK
dc.relation.ispartofIEEE Transactions on Intelligent Transportation Systemsen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectFeature-point extractionen_HK
dc.subjectImage segmentationen_HK
dc.subjectTexture analysisen_HK
dc.subjectVehicle occlusionen_HK
dc.subjectVehicle-component identificationen_HK
dc.titleVehicle-component identification based on multiscale textural couriersen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1524-9050&volume=8&issue=4&spage=681&epage=694&date=2007&atitle=Vehicle-component+identification+based+on+multiscale+texture+couriersen_HK
dc.identifier.emailYung, NHC:nyung@eee.hku.hken_HK
dc.identifier.authorityYung, NHC=rp00226en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TITS.2007.908144en_HK
dc.identifier.scopuseid_2-s2.0-36849085445en_HK
dc.identifier.hkuros143213-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-36849085445&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume8en_HK
dc.identifier.issue4en_HK
dc.identifier.spage681en_HK
dc.identifier.epage694en_HK
dc.identifier.isiWOS:000251589900012-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLam, WWL=16836339900en_HK
dc.identifier.scopusauthoridPang, CCC=7201425202en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK

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